SpdMatrix sum_self_transpose(const Mat &A){
assert(A.is_square());
uint n = A.nrow();
Spd ans(n, 0.0);
for(uint i=0; i<n; ++i){
for(uint j=0; j<i; ++j){
ans(i,j) = ans(j,i) = A(i,j) + A(j,i);}}
return ans;
}
SpdMatrix chol2inv(const Mat &L){
assert(L.is_square());
int n = L.nrow();
SpdMatrix ans(L, false);
int info=0;
dpotri_("L", &n, ans.data(), &n, &info);
for(int i=0; i<n; ++i){
for(int j=0; j<i; ++j){
ans(j,i) = ans(i,j);}}
return ans;
}
inline
void
op_trimat::apply_htrans
(
Mat<eT>& out,
const Mat<eT>& A,
const bool upper,
const typename arma_cx_only<eT>::result* junk
)
{
arma_extra_debug_sigprint();
arma_ignore(junk);
arma_debug_check( (A.is_square() == false), "trimatu()/trimatl(): given matrix must be square sized" );
const uword N = A.n_rows;
if(&out != &A)
{
out.copy_size(A);
}
if(upper)
{
// Upper triangular: but since we're transposing, we're taking the lower
// triangular and putting it in the upper half.
for(uword row = 0; row < N; ++row)
{
eT* out_colptr = out.colptr(row);
for(uword col = 0; col <= row; ++col)
{
//out.at(col, row) = std::conj( A.at(row, col) );
out_colptr[col] = std::conj( A.at(row, col) );
}
}
}
else
{
// Lower triangular: but since we're transposing, we're taking the upper
// triangular and putting it in the lower half.
for(uword row = 0; row < N; ++row)
{
for(uword col = row; col < N; ++col)
{
out.at(col, row) = std::conj( A.at(row, col) );
}
}
}
op_trimat::fill_zeros(out, upper);
}
inline
bool
op_chol::apply_direct(Mat<typename T1::elem_type>& out, const Base<typename T1::elem_type,T1>& A_expr, const uword layout)
{
arma_extra_debug_sigprint();
out = A_expr.get_ref();
arma_debug_check( (out.is_square() == false), "chol(): given matrix must be square sized" );
if(out.is_empty()) { return true; }
uword KD = 0;
const bool is_band = (auxlib::crippled_lapack(out)) ? false : ((layout == 0) ? band_helper::is_band_upper(KD, out, uword(32)) : band_helper::is_band_lower(KD, out, uword(32)));
const bool status = (is_band) ? auxlib::chol_band(out, KD, layout) : auxlib::chol(out, layout);
return status;
}
inline
void
op_trimat::apply_htrans
(
Mat<eT>& out,
const Mat<eT>& A,
const bool upper,
const typename arma_not_cx<eT>::result* junk
)
{
arma_extra_debug_sigprint();
arma_ignore(junk);
// This specialisation is for trimatl(trans(X)) = trans(trimatu(X)) and also
// trimatu(trans(X)) = trans(trimatl(X)). We want to avoid the creation of an
// extra temporary.
// It doesn't matter if the input and output matrices are the same; we will
// pull data from the upper or lower triangular to the lower or upper
// triangular (respectively) and then set the rest to 0, so overwriting issues
// aren't present.
arma_debug_check( (A.is_square() == false), "trimatu()/trimatl(): given matrix must be square sized" );
const uword N = A.n_rows;
if(&out != &A)
{
out.copy_size(A);
}
// We can't really get away with any array copy operations here,
// unfortunately...
if(upper)
{
// Upper triangular: but since we're transposing, we're taking the lower
// triangular and putting it in the upper half.
for(uword row = 0; row < N; ++row)
{
eT* out_colptr = out.colptr(row);
for(uword col = 0; col <= row; ++col)
{
//out.at(col, row) = A.at(row, col);
out_colptr[col] = A.at(row, col);
}
}
}
else
{
// Lower triangular: but since we're transposing, we're taking the upper
// triangular and putting it in the lower half.
for(uword row = 0; row < N; ++row)
{
for(uword col = row; col < N; ++col)
{
out.at(col, row) = A.at(row, col);
}
}
}
op_trimat::fill_zeros(out, upper);
}
